activity
20162022
most citedMeDAL: Medical Abbreviation Disambiguation Dataset for Natural Language Understanding Pretraining

25 citations · 80 across the 9 of their papers we have counts for

collaborators

18 papers

cs.CL20221 cited

The Curious Case of Absolute Position Embeddings

Koustuv Sinha, Amirhossein Kazemnejad, Siva Reddy +3

Transformer language models encode the notion of word order using positional information. Most commonly, this positional information is represented by absolute position embeddings…

cs.CL202213 cited

On the Origin of Hallucinations in Conversational Models: Is it the Datasets or the Models?

Nouha Dziri, Sivan Milton, Mo Yu +2

Knowledge-grounded conversational models are known to suffer from producing factually invalid statements, a phenomenon commonly called hallucination. In this work, we investigate t…

cs.LG202217 cited

Combining Modular Skills in Multitask Learning

Edoardo M. Ponti, Alessandro Sordoni, Yoshua Bengio +1

A modular design encourages neural models to disentangle and recombine different facets of knowledge to generalise more systematically to new tasks. In this work, we assume that ea…

cs.CL20211 cited

Visually Grounded Reasoning across Languages and Cultures

Fangyu Liu, Emanuele Bugliarello, Edoardo Maria Ponti +3

The design of widespread vision-and-language datasets and pre-trained encoders directly adopts, or draws inspiration from, the concepts and images of ImageNet. While one can hardly…

cs.CL202110 cited

Modelling Latent Translations for Cross-Lingual Transfer

Edoardo Maria Ponti, Julia Kreutzer, Ivan Vulić +1

While achieving state-of-the-art results in multiple tasks and languages, translation-based cross-lingual transfer is often overlooked in favour of massively multilingual pre-train…

cs.CL2021

Minimax and Neyman-Pearson Meta-Learning for Outlier Languages

Edoardo Maria Ponti, Rahul Aralikatte, Disha Shrivastava +2

Model-agnostic meta-learning (MAML) has been recently put forth as a strategy to learn resource-poor languages in a sample-efficient fashion. Nevertheless, the properties of these…